David Silver

British computer scientist at University College London and a leader of deep reinforcement learningdeep reinforcement learning, n.: Reinforcement learning in which a large neural network does the learning, letting an AI learn tasks such as video games or robot control directly from raw inputs like screen pixels or camera images.. He co-founded the games company Elixir Studios with Demis HassabisDemis Hassabis, prop. n.: A British AI researcher and former chess prodigy who co-founded DeepMind, led the teams behind AlphaGo and AlphaFold, and shared the 2024 Nobel Prize in Chemistry., then earned a PhD at the University of Alberta (2009) under Richard SuttonRichard Sutton, prop. n.: A Canadian computer scientist who, with Andrew Barto, laid the groundwork for teaching machines by trial, error and reward, and whose essay 'The Bitter Lesson' argues that methods that scale with computing power always win. on reinforcement learning and Monte Carlo tree searchMonte Carlo tree search, n.: A way for a game-playing program to choose a move by simulating many possible continuations, focusing on the most promising lines, and picking the move that worked out best on average. in Go. Working with DeepMind from its founding in 2010, full-time from 2013, he led its reinforcement-learning research, including AlphaGoAlphaGo, prop. n.: A DeepMind program that in 2016 beat Lee Sedol, one of the world's best players of the board game Go, a decade or more before many experts expected a computer to manage it., which combined policy and value networks with tree search to defeat Lee Sedol in 2016; AlphaGo ZeroAlphaGo Zero, prop. n.: A program from DeepMind that taught itself to play the board game Go better than any human in 2017, starting from nothing but the rules and learning only by playing millions of games against itself. and AlphaZeroAlphaZero, prop. n.: A 2017 DeepMind program that taught itself chess, shogi and Go from nothing but the rules by playing against itself, and within hours of training beat the strongest existing programs. (2017), which learned by self-playself-play, n.: Training an AI by having it play against copies of itself, so it always has an opponent at its own level and can keep improving without human examples. alone; and MuZero (2019), which also learned its own model of the game. With Sutton he argued in 2025 that AI must increasingly learn from its own experience of the world (see era of experienceera of experience, n.: The prediction, made by David Silver and Richard Sutton in 2025, that AI will soon learn mainly from its own experience of acting in the world rather than from human-written data.). In January 2026 he left Google DeepMind to lead Ineffable Intelligence, his London startup pursuing superintelligence through reinforcement learning. ACM Prize in Computing 2019.